Implementation of Different Machine Learning Projects Using Scikit-learn and Tensorflow Frameworks

Abstract

In this study, the solution of classification, regression, and time series problems used in different fields with Scikit-learn and TensorFlow libraries using Python programming language is discussed. Four projects are carried out. The first project addressed the classification problem. The performance of the models is evaluated by using classical machine learning techniques and deep neural networks to solve the classification problem. The second project considered is the regression problem. The White Wine Quality dataset is used to understand the regression problem. The third project is the image classification problem. Image classification is one of the essential areas of study in recent years. Classification of images is achieved with CNN, one of the deep learning techniques. Keras and TensorFlow libraries are used in CNN. The last project discussed is the estimation of the closing value of the stock market stock.